Harnessing solar power with adaptive control of PV-enriched microgrids using A3C-driven deep reinforcement learning

IF 2 4区 工程技术 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC
Yaohua Liao, Xin Jin, Zhiming Gu, Bo Li, Tingzhe Pan
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引用次数: 0

Abstract

This research introduces an advanced adaptive control framework utilizing deep reinforcement learning, specifically the Asynchronous Advantage Actor-Critic algorithm, to optimize the operation of photovoltaic-enriched microgrids integrated with solar electric vehicles. The integration of solar electric vehicles within microgrids not only addresses transportation needs and energy sustainability by acting as dynamic energy storage systems. The inherent intermittency of solar power and the dynamic energy demands of solar electric vehicles pose significant operational challenges, requiring robust, flexible control systems capable of real-time optimization. Our framework leverages the Asynchronous Advantage Actor-Critic algorithm for its efficiency in handling high-dimensional state spaces and its capability for rapid, concurrent learning processes, making it well-suited for the dynamic and complex environment of photovoltaic-enriched microgrids. The proposed model innovatively combines solar energy generation with solar electric vehicle energy storage and consumption dynamics, providing a holistic approach to microgrid management that optimizes energy flows, reduces reliance on traditional energy sources, and minimizes environmental impact.

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来源期刊
Iet Generation Transmission & Distribution
Iet Generation Transmission & Distribution 工程技术-工程:电子与电气
CiteScore
6.10
自引率
12.00%
发文量
301
审稿时长
5.4 months
期刊介绍: IET Generation, Transmission & Distribution is intended as a forum for the publication and discussion of current practice and future developments in electric power generation, transmission and distribution. Practical papers in which examples of good present practice can be described and disseminated are particularly sought. Papers of high technical merit relying on mathematical arguments and computation will be considered, but authors are asked to relegate, as far as possible, the details of analysis to an appendix. The scope of IET Generation, Transmission & Distribution includes the following: Design of transmission and distribution systems Operation and control of power generation Power system management, planning and economics Power system operation, protection and control Power system measurement and modelling Computer applications and computational intelligence in power flexible AC or DC transmission systems Special Issues. Current Call for papers: Next Generation of Synchrophasor-based Power System Monitoring, Operation and Control - https://digital-library.theiet.org/files/IET_GTD_CFP_NGSPSMOC.pdf
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